Member of Technical Staff: Engineer, Simulation Content Authoring

Walden Robotics•San Francisco, CA

68d•$213,750 - $285,000

About The Position

We’re looking for a motivated, hands-on engineer to build simulation content pipelines that create rich, diverse, and useful environments for evaluating and improving robot policies. You’ll design production-quality systems for generating, managing, validating, and deploying scenes, assets, and scenarios at scale. As a Member of Technical Staff, you’ll own substantial parts of the simulation-content authoring stack and ensure they integrate cleanly with the broader simulation platform.

Requirements

2+ years of relevant experience
Strong software engineering fundamentals and experience designing, building, and maintaining substantial software systems.
Experience building simulation-ready 3D assets, with strong judgment about visual and collision geometry, including trade-offs among fidelity, physical accuracy, and runtime performance.
Up-to-date knowledge of advances in simulation-ready asset and scene generation, with the ability to evaluate state-of-the-art methods and apply them pragmatically.
Ability to own ambiguous problem areas from initial design through production deployment.

Nice To Haves

Familiarity with agentic systems and LLM-driven developer tooling.
Experience with robotics simulation, robot learning, and automated policy evaluation.
Familiarity with simulation platforms such as Isaac Sim, MuJoCo, or Drake.

Responsibilities

Design and build scalable systems for authoring simulation scenes, assets, and evaluation scenarios.
Define simulation tasks and scenarios that reflect real robotics priorities and expose policy weaknesses.
Develop workflows that make simulation content composable, editable, reproducible, and easy to deploy.
Build generation and curation pipelines that combine procedural methods, asset libraries, human input, and agentic workflows.
Create validation and quality-control systems for geometry, physical properties, articulation, scene composition, and task relevance.